accuracy.MC

This function allows you to estimate assignment accuracies of Monte-Carlo cross-validation results. The output results can be used to make assignment accuracy plots (use function accuracy.plot).

Use Monte-Carlo and K-fold cross-validation coupled with machine-
learning classification algorithms to perform population assignment, with
functionalities of evaluating discriminatory power of independent training
samples, identifying informative loci, reducing data dimensionality for genomic
data, integrating genetic and non-genetic data, and visualizing results.

Kuan-Yu Chen

assignPOP

Population Assignment using Genetic, Non-Genetic or Integrated
Data in a Machine Learning Framework

accuracy.MC function

<dl><dt>dir</dt>
<dd>A character string to specify the folder that has your Monte-Carlo cross-validation results. A slash should be included at the end (e.g., dir="YourFolderName/").</dd></dl>

Arguments

Estimate assignment accuracies of Monte-Carlo cross-validation results — accuracy.MC

<dl>

<dt>dir</dt>
<dd>A character string to specify the folder that has your Monte-Carlo cross-validation results. A slash should be included at the end (e.g., dir="YourFolderName/").</dd>

</dl>

accuracy.MC: Estimate assignment accuracies of Monte-Carlo cross-validation results

Description

Usage

Value

Arguments